DyMEP (version 0.1.2)

best_DyMEP_model: A function to get the best model with the environmental covariates at hand

Description

A function to get the best model with the environmental covariates at hand

Usage

best_DyMEP_model(
  env_covariates,
  pheno_phases,
  crop_abbrev,
  skillscore_to_select = "RMSE",
  return_just_best = TRUE,
  output_list_for_prediction = FALSE
)

Value

dataframe with the best models selected for the given input arguments

Arguments

env_covariates

the environmental covariates you have at hand; inputs as character strings naming the available environmental covariate

pheno_phases

the phenological phases you are interested in. Input as character string, available phenological phases do depend on the chosen crop (use available_crops_and_phases())

crop_abbrev

the abbreviation of the wanted crop

skillscore_to_select

the skillscore according to which you want to select (Default = "RMSE); available options: "RMSE", "MAE", "cor", "AIC" and "SumLogLikelihood"

return_just_best

decide whether you want to get a list of all potential options back, or just the best (default = TRUE)

output_list_for_prediction

boolean (TRUE/FALSE), if TRUE the output of this function is a list which can directly be used for the pheno_phase_prediction function as input (phase_covariate_list). Select return_just_best also as TRUE if this output is wished

Fields

abbrev

Description of crop_abbrev column.

pheno_phase

Description of pheno_phase column.

Examples

best_DyMEP_model(env_covariates =  c("tas","VPD"),
      pheno_phases = c("sowing-emergence"),
      crop_abbrev = "WW")